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Buckle: Evaluating Fact Checking Algorithms Built on Knowledge Bases

Summary: BUCKLE is an open-source benchmark for evaluating fact-checking algorithms on knowledge bases in a fair, controlled setting. It shows how training/test fact properties and reference data shape performance and compares approaches, including link-prediction methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h582f3b97f70f47a4
Venue
VLDB
Year
2019
Pagerank
5.4546499e-05
Overall Rank
7,777 | 47.72%
DOI
10.14778/3352063.3352069

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{huynh_vldb19,
        title = {{Buckle: Evaluating Fact Checking Algorithms Built on Knowledge Bases}},
        author = {Huynh, Viet-Phi and Papotti, Paolo},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {12},
        pages = {1798--1801},
        doi = {10.14778/3352063.3352069},
        url = {https://doi.org/10.14778/3352063.3352069},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,149 Demonstrating CEDAR: A System for Cost-Efficient Data-Driven Claim Verification 2025 SIGMOD 4.9793485e-05
11,364 CEDAR: A System for Cost-Efficient Data-Driven Claim Verification 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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